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Perceived health risks of 3G cell phones: do users care?

Published: 01 June 2007 Publication History

Abstract

Studying the perception of health risks associated with mobile phones and the implications for usage.

References

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Brooker, G. An assessment of an expanded measure of perceived risk. Advances in Consumer Research 11, (1984), 439--441.
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Davis, F. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13, 3 (Sept. 1989), 319--340.
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Featherman, M. and Pavlou, P. Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human Computer Studies 59, 1 (2003), 451--474.
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Finucane, M.L., Slovic, P., Mertz, C.K., Flynn, J., and Satterfield, T.A. Gender, race, and perceived risk: The `white male' effect. Health, Risk, and Society 2, 2 (2000), 159--172.
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Lim, N. Consumers' perceived risk: Sources versus consequences. Electronic Commerce Research and Applications 2, 3 (2003), 216--228.

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Published In

cover image Communications of the ACM
Communications of the ACM  Volume 50, Issue 6
Smart business networks
June 2007
84 pages
ISSN:0001-0782
EISSN:1557-7317
DOI:10.1145/1247001
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 2007
Published in CACM Volume 50, Issue 6

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Cited By

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  • (2024)A systematic review of conversational AI tools in ELT: Publication trends, tools, research methods, learning outcomes, and antecedentsComputers and Education: Artificial Intelligence10.1016/j.caeai.2024.100291(100291)Online publication date: Sep-2024
  • (2023)Fragile Effects of Mobile Phone Emitted Radiations on Agricultural Growth and Ecological SystemsReviews in Agricultural Science10.7831/ras.11.0_13711(137-155)Online publication date: 2023
  • (2023)Factors affecting parental intention to use AI-based social robots for children’s ESL learningEducation and Information Technologies10.1007/s10639-023-12023-w29:5(6059-6086)Online publication date: 27-Jul-2023
  • (2018)Understanding the diffusion of virtual reality glasses: The role of media, fashion and technologyTechnological Forecasting and Social Change10.1016/j.techfore.2018.09.008Online publication date: Sep-2018
  • (2018)Skewing users’ rational risk considerations in social commerce: An empirical examination of the role of social identificationInformation & Management10.1016/j.im.2018.05.00855:8(1038-1048)Online publication date: Dec-2018
  • (2017)A trust-risk perspective on social commerce use: an examination of the biasing role of habitInternet Research10.1108/IntR-06-2016-017527:3(586-607)Online publication date: 5-Jun-2017
  • (2017)Sustainable perspectives on energy consumption, EMRF, environment, health and accident risks associated with the use of mobile phonesRenewable and Sustainable Energy Reviews10.1016/j.rser.2016.09.01167(192-206)Online publication date: Jan-2017
  • (2016)Environmental and health aspects of mobile phone production and use: Suggestions for innovation and policyEnvironmental Innovation and Societal Transitions10.1016/j.eist.2016.04.00221(69-79)Online publication date: Dec-2016
  • (2014)Adoption of Mobile Telephony in Rural India: An Empirical StudyDecision Sciences10.1111/deci.1206845:2(281-307)Online publication date: 20-Apr-2014
  • (2012)Role of user a priori attitude in the acceptance of mobile health: an empirical investigationElectronic Markets10.1007/s12525-012-0111-523:1(15-27)Online publication date: 29-Nov-2012
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